As computer processors have evolved over time they have gained the capability to execute more tasks by multitasking and the capability to execute tasks faster by operating at higher clock frequencies. However, as the processors have developed additional processing power, their power consumption has also risen. For example, a processor's power consumption may be proportional to the clock speed at which the processor operates. Thus, when the processor operates at higher clock speeds to execute tasks faster, the processor consumes more power than when the processor is operating at a lower clock speed. Power consumption may be a particular problem in a computer datacenter where hundreds or thousands of computers are located, such as a computer datacenter for providing cloud services to remote computers.
One conventional solution for reducing power consumption is dynamic voltage scaling (DVS), which reduces an operating frequency and/or operating power supply voltage for the processor when demand on the processor to execute tasks is low. Although this conventional technique may reduce power consumption of the processor, it does so at the risk of not completing tasks assigned to the processor by the tasks' deadlines. That is, this technique is generally agnostic to the priority of the task.
Another conventional solution is reliability aware power management (RAPM), which schedules tasks to maintain original reliability. Original reliability may be defined as the probability of completing all tasks successfully when executed at the processor's maximum frequency. In RAPM, jobs are scheduled on a processor running at a scaled down frequency and a corresponding recovery job is scheduled. When the first job completes, an acceptance test is performed. If the job completed successfully, then the recovery job is cancelled. Otherwise, the recovery job is executed on the processor at a maximum frequency. However, in the event that the first job failed, the recovery job may not complete before the deadline. Thus, processors executing according to the RAPM technique may not handle jobs with a utilization factor of more than 50%.